Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/nicepkg/ai-workflow/launch-gtm-executionnpx skills add nicepkg/ai-workflow --skill launch-gtm-executiongit clone --depth 1 https://github.com/nicepkg/ai-workflowWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00031 | $0.02366 |
| Opus 5 | $0.00015 | $0.01183 |
| Sonnet 5 | $0.00006 | $0.00473 |
| Haiku 4.5 | $0.00003 | $0.00237 |
Grade A, and why
launch-gtm-execution scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 383 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Launch & Go-To-Market Skill
Master the art of successful product launches. From GTM strategy through launch execution, learn to coordinate teams, build momentum, and achieve market success.
Go-To-Market (GTM) Strategy
GTM Framework Decision
1. Direct Sales Model
- Your team directly sells to customers
- Best for: High ACV (>$10K), complex product
- Sales cycle: 3-6 months
- Team size: 1 AE per $500K-$1M ARR target
- Examples: Salesforce, HubSpot, Workday
Pros:
- Control over message
- Deep customer relationships
- Higher deal size possible
- Custom solutions
Cons:
- Expensive ($200K+ per rep)
- Slower to scale
- Long sales cycles
- Small addressable market needed for ROI
Key Metrics:
- Sales Qualified Lead (SQL)
- Close rate (typically 20-40%)
- Sales cycle length
- Customer Acquisition Cost (CAC)
2. Self-Service / Freemium Model
- Customers discover and sign up themselves
- Best for: Low ACV (<$1K), self-explanatory product
- Sales cycle: Minutes to days
- Team: Product + Marketing focused
Pros:
- Scales without sales team
- Low CAC
- Fast adoption
- Land and expand opportunity
Cons:
- High churn risk
- Need viral/network effects
- Requires excellent product
- Difficult to reach enterprise
Key Metrics:
- Free-to-paid conversion (2-5% target)
- Monthly Recurring Revenue (MRR)
- Customer Lifetime Value (LTV)
- CAC < 30% LTV
3. Sales Development (SMB)
- SDR/AE team for smaller deals
- Best for: SMB market ($2K-$50K ACV)
- Sales cycle: 1-3 months
- Lower cost than enterprise sales
Pros:
- Better ROI than enterprise sales
- Faster sales cycles
- Larger addressable market
- Still personal touch
Cons:
- Volume required
- Lower margins
- Churn challenges
4. Channel/Partner Model
- Resellers, integrations, platforms
- Best for: Reaching wide market cheaply
- Examples: App stores, Zapier, AWS Marketplace
Pros:
- Low CAC (partner pays)
- Wide distribution
- Established customer relationships
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 383 lines · 31 tokens per session scan A 939ab9e285cd
launch-gtm-execution is a skill published in the GitHub repository nicepkg/ai-workflow (283 stars, last pushed 7mo ago), licensed MIT. It adds 31 tokens to every session and 2,366 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
aatmf-t10-confidentiality-breach
AATMF T10 — Integrity & Confidentiality Breach. System prompt extraction, training-data extraction, model-weight leakage, private-key recovery.
publish-registry
Publish @agentos-software/ registry packages from AgentOS. Use whenever the user asks to publish or release registry software/agent packages.
mochi-remind
Handle due reminders — notify the user with natural language and mark them done.
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
lazarus-group
Adversary-emulation profile for Lazarus Group (G0032, aka Hidden Cobra / Diamond Sleet / Labyrinth Chollima), a North Korean RGB-linked actor conducting espionage, destructive, and financially motivated operations.
sidewinder-rattlesnake
Adversary-emulation profile for SideWinder (G0121 / Rattlesnake / T-APT-04 / Razor Tiger), India's suspected state-sponsored cyber-espionage actor.